The work performed in a genetic testing laboratory to process a sample requires many detailed-oriented steps and a wealth of individual and institutional knowledge. The output of this process often has a significant impact on patient outcomes and wellbeing. At the same time, the work is repetitive and requires the handling of large test volumes under the time pressures inherent in medical procedures. This is particularly the case with next- generation sequencing (NGS) based tests, which are increasingly used to diagnose rare diseases, analyze mutation profiles of tumors, offer reproductive genetic services and perform newborn genetic screening. Existing software solution in this space have taken steps to make the overall work for a clinician simpler. Still, the efforts have not addressed the dependency on expert judgment and the following of detailed and often complex procedures to complete a genetic test. This environment lends itself to the application of workflow automation capabilities. The key benefits for the clinical users are the following: 1. Minimizing the potential for error: Workflow automation prevents essential and necessary tasks from going unnoticed. With tasks and the personnel that perform them being compressively tracked, workflow automation saves labs from far reaching and potentially very costly expenses associated with lab personnel errors. 2. Reducing costs and increasing throughput: Integrating internal communication into the workflow platform reduces the overhead required to conduct clinical work and stay compliant. The result is more work can be done with the same personnel. 3. Creating accountability and reducing subjectivity: As the complex rules and institutional knowledge of a laboratory gets codified into a workflow, every analytical step can be assigned and attributed to individual lab personnel while reducing the amount of choices made outside the system also reduces variance of outcomes attributed to operator subjectivity. In this project, we will bring all elements of the clinical workflow for next-generation sequencing together. This includes the detection of single nucleotide variations and copy number variations, the annotation and clinical assessment of those variants, the storing of the finalized report and all associated data in a genetic data warehouse. This project will also cover the automation of the informatics that enable a decision support system capable of implementing variant classification guidelines such as those by the American College of Medical Genetics and other leading industry bodies.